使用R和ggplot2绘制金字塔图

Question

我需要绘制一个金字塔图,就像附图一样.

我从这里找到了一个使用R(但不是ggplot)的例子,有人能给我一些使用ggplot做这个的暗示吗？谢谢!

Answer 1

这本质上是背靠背的条形图,类似于ggplot2在优秀的学习者博客中使用的条形图:http://learnr.wordpress.com/2009/09/24/ggplot2-back-to-back-bar-charts /

您可以使用coord_flip其中一个图,但我不知道如何让它在两个图之间共享y轴标签,就像您上面所做的那样.下面的代码应该让你足够接近原始:

首先创建一个数据样本数据框,将Age列转换为具有所需断点的因子:

require(ggplot2)
df <- data.frame(Type = sample(c('Male', 'Female', 'Female'), 1000, replace=TRUE),
                 Age = sample(18:60, 1000, replace=TRUE))

AgesFactor <- ordered( cut(df$Age, breaks = c(18,seq(20,60,5)), 
                           include.lowest = TRUE))

df$Age <- AgesFactor

现在开始构建情节:使用相应的数据子集创建男性和女性情节,抑制图例等.

gg <- ggplot(data = df, aes(x=Age))

gg.male <- gg + 
  geom_bar( subset = .(Type == 'Male'), 
            aes( y = ..count../sum(..count..), fill = Age)) +
  scale_y_continuous('', formatter = 'percent') + 
  opts(legend.position = 'none') +
  opts(axis.text.y = theme_blank(), axis.title.y = theme_blank()) + 
  opts(title = 'Male', plot.title = theme_text( size = 10) ) +  
  coord_flip()    

对于女性情节,使用trans = "reverse"...... 反转'百分比'轴

gg.female <- gg + 
  geom_bar( subset = .(Type == 'Female'), 
            aes( y = ..count../sum(..count..), fill = Age)) +
  scale_y_continuous('', formatter = 'percent', trans = 'reverse') + 
  opts(legend.position = 'none') +
  opts(axis.text.y = theme_blank(), 
       axis.title.y = theme_blank(), 
       title = 'Female') +
  opts( plot.title = theme_text( size = 10) ) +
  coord_flip()

现在创建一个用于显示年龄括号的图geom_text,但也使用一个虚拟图geom_bar来确保此图中"年龄"轴的缩放与男性和女性图中的相同:

gg.ages <- gg + 
  geom_bar( subset = .(Type == 'Male'), aes( y = 0, fill = alpha('white',0))) +
  geom_text( aes( y = 0,  label = as.character(Age)), size = 3) +
  coord_flip() +
  opts(title = 'Ages',
       legend.position = 'none' ,
       axis.text.y = theme_blank(),
       axis.title.y = theme_blank(),
       axis.text.x = theme_blank(),
       axis.ticks = theme_blank(),          
       plot.title = theme_text( size = 10))       

最后,使用Hadley Wickham的书中的方法将图块排列在网格上:

grid.newpage()

pushViewport( viewport( layout = grid.layout(1,3, widths = c(.4,.2,.4))))

vplayout <- function(x, y) viewport(layout.pos.row = x, layout.pos.col = y)

print(gg.female, vp = vplayout(1,1))
print(gg.ages,   vp = vplayout(1,2))
print(gg.male,   vp = vplayout(1,3))

Answer 2

我做了一些解决方法 - 而不是使用geom_bar,我使用geom_linerange和geom_label.

library(magrittr)
library(dplyr)
library(ggplot2)

population <- read.csv("https://raw.githubusercontent.com/andriy-gazin/datasets/master/ageSexDistribution.csv")

population %<>% 
  tidyr::gather(sex, number, -year, - ageGroup) %>% 
  mutate(ageGroup = gsub("100 ? ??????", "?100", ageGroup), 
     ageGroup = factor(ageGroup,
                        ordered = TRUE,
                        levels = c("0-4", "5-9", "10-14", "15-19", "20-24",
                                   "25-29", "30-34", "35-39", "40-44", 
                                   "45-49", "50-54", "55-59", "60-64",
                                   "65-69", "70-74", "75-79", "80-84",
                                   "85-89", "90-94", "95-99", "?100")),
     number = ifelse(sex == "male", number*-1/10^6, number/10^6)) %>% 
  filter(year %in% c(1990, 1995, 2000, 2005, 2010, 2015))

png(filename = "~/R/pyramid.png", width = 900, height = 1000, type = "cairo")

ggplot(population, aes(x = ageGroup, color = sex))+
  geom_linerange(data = population[population$sex=="male",], 
                 aes(ymin = -0.3, ymax = -0.3+number), size = 3.5, alpha = 0.8)+
  geom_linerange(data = population[population$sex=="female",], 
                 aes(ymin = 0.3, ymax = 0.3+number), size = 3.5, alpha = 0.8)+
  geom_label(aes(x = ageGroup, y = 0, label = ageGroup, family = "Ubuntu Condensed"), 
         inherit.aes = F,
         size = 3.5, label.padding = unit(0.0, "lines"), label.size = 0,
         label.r = unit(0.0, "lines"), fill = "#EFF2F4", alpha = 0.9, color = "#5D646F")+
  scale_y_continuous(breaks = c(c(-2, -1.5, -1, -0.5, 0) + -0.3, c(0, 0.5, 1, 1.5, 2)+0.3),
                 labels = c("2", "1.5", "1", "0.5", "0", "0", "0.5", "1", "1.5", "2"))+
  facet_wrap(~year, ncol = 2)+
  coord_flip()+
labs(title = "???????? ????????? ???????",
   subtitle = "???????-?????? ????? ? 1990-2015 ?????, ??? ????",
   caption = "????: ??????????? ???????")+
  scale_color_manual(name = "", values = c(male = "#3E606F", female = "#8C3F4D"),
                 labels = c("?????", "????????"))+
  theme_minimal(base_family = "Ubuntu Condensed")+
theme(text = element_text(color = "#3A3F4A"),
    panel.grid.major.y = element_blank(),
    panel.grid.minor = element_blank(),
    panel.grid.major.x = element_line(linetype = "dotted", size = 0.3, color = "#3A3F4A"),
    axis.title = element_blank(),
    plot.title = element_text(face = "bold", size = 36, margin = margin(b = 10), hjust = 0.030),
    plot.subtitle = element_text(size = 16, margin = margin(b = 20), hjust = 0.030),
    plot.caption = element_text(size = 14, margin = margin(b = 10, t = 50), color = "#5D646F"),
    axis.text.x = element_text(size = 12, color = "#5D646F"),
    axis.text.y = element_blank(),
    strip.text = element_text(color = "#5D646F", size = 18, face = "bold", hjust = 0.030),
    plot.background = element_rect(fill = "#EFF2F4"),
    plot.margin = unit(c(2, 2, 2, 2), "cm"),
    legend.position = "top",
    legend.margin  = unit(0.1, "lines"),
    legend.text  = element_text(family = "Ubuntu Condensed", size = 14),
    legend.text.align = 0)

dev.off()

这是由此产生的情节:

Answer 3

稍微调整一下:

library(ggplot2)
library(plyr)
library(gridExtra)

## The Data
df <- data.frame(Type = sample(c('Male', 'Female', 'Female'), 1000, replace=TRUE),
    Age = sample(18:60, 1000, replace=TRUE))

AgesFactor <- ordered(cut(df$Age, breaks = c(18,seq(20,60,5)), 
     include.lowest = TRUE))

df$Age <- AgesFactor

## Plotting
gg <- ggplot(data = df, aes(x=Age))

gg.male <- gg + 
    geom_bar( data=subset(df,Type == 'Male'), 
        aes( y = ..count../sum(..count..), fill = Age)) +
    scale_y_continuous('', labels = scales::percent) + 
    theme(legend.position = 'none',
        axis.title.y = element_blank(),
        plot.title = element_text(size = 11.5),
        plot.margin=unit(c(0.1,0.2,0.1,-.1),"cm"),
        axis.ticks.y = element_blank(), 
        axis.text.y = theme_bw()$axis.text.y) + 
    ggtitle("Male") + 
    coord_flip()    

gg.female <-  gg + 
    geom_bar( data=subset(df,Type == 'Female'), 
        aes( y = ..count../sum(..count..), fill = Age)) +
    scale_y_continuous('', labels = scales::percent, 
                   trans = 'reverse') + 
    theme(legend.position = 'none',
        axis.text.y = element_blank(),
        axis.ticks.y = element_blank(), 
        plot.title = element_text(size = 11.5),
        plot.margin=unit(c(0.1,0,0.1,0.05),"cm")) + 
    ggtitle("Female") + 
    coord_flip() + 
    ylab("Age")

## Plutting it together
grid.arrange(gg.female,
    gg.male,
    widths=c(0.4,0.6),
    ncol=2
)

我仍然想要更多地利用边距(也许panel.margin会有助于theme通话).

Answer 4

我已经使用了facet_wrap()相当多的面板表来在不同的方面获得镜像轴 - 我认为结果非常适合人口金字塔。您可以在此处查看代码。

然后，使用facet_share()函数：

library(magrittr)
library(ggpol)

population <- read.csv("https://raw.githubusercontent.com/andriy-gazin/datasets/master/ageSexDistribution.csv", encoding = "UTF-8")

population %<>% 
  mutate(ageGroup = factor(ageGroup, levels = ageGroup[seq(length(levels(ageGroup)))])) %>%
  filter(year == 2015) %>%
  mutate(male = male * -1) %>% 
  gather(gender, count, -year, -ageGroup) %>%
  mutate(gender = factor(gender, levels = c("male", "female"))) %>%
  filter(ageGroup != "100 ? ??????")

ggplot(population, aes(x = ageGroup, y = count, fill = gender)) +
  geom_bar(stat = "identity") + 
  facet_share(~gender, dir = "h", scales = "free", reverse_num = TRUE) +
  coord_flip() +
  theme_minimal()